论文部分内容阅读
基于自适应噪声对消技术及人工神经网络（ＡＮＮ）理论，提出了一种谐波电流动态检测方法。所设计的谐波检测系统采取在线学习、二级ＡＮＮ滤波技术，能检测出所设定的ｎ次（如３、５、７次等）谐波电流及剩余的谐波总电流，并能同时测出基波有功、无功电流和基波位移因数。仿真结果证实，该系统所测出的各项参数与实际值的相移和畸变非常小，且系统的结构简单，计算量小。该方法可应用于有源滤波或混合有源滤波的谐波及无功补偿。
Based on the adaptive noise canceling technique and artificial neural network (ANN) theory, a harmonic current dynamic detection method is proposed. The design of harmonic detection system to take online learning, two ANN filtering technology, can detect the set of n times (such as 3,5,7 times, etc.) of the harmonic current and the remaining harmonic current, and can simultaneously measure Fundamental wave active, reactive current and fundamental wave displacement factor. The simulation results confirm that the phase shift and distortion of each parameter measured by the system and the actual value are very small, and the structure of the system is simple and the calculation amount is small. The method can be applied to harmonic and reactive power compensation of active filter or hybrid active filter.